For more details on registrations and submissions for the Neural networks and deep learning, please first login to your account. If you do not have an account then you can create one below:
This is a comprehensive one-day workshop providing a foundational understanding of deep learning concepts and practical skills in building and evaluating neural network models. The course is split into a morning session covering the theoretical framework of neural networks, activation functions and regularization techniques, followed by an afternoon of hands-on exercises. Practical sessions will cover supervised learning applications, specifically image classification using Feedforward Networks and time series forecasting using Recurrent Neural Networks (RNNs) and Long Short-Term Memory networks (LSTMs).
Venue Address: Bank Ċentrali ta’ Malta – Central Bank of Malta; Pjazza Kastilja, Valletta VLT 1060, Malta
Lecturer, University of Malta, AI Department. Research on tensor-based machine learning methods. Published extensively.
Dr Konstantinos Makantasis is a lecturer in the Department of Artificial Intelligence at the University of Malta. He holds a Diploma in Computer Engineering as well as MSc and PhD degrees from the Technical University of Crete in Greece. In 2020, he was awarded the prestigious Marie Skłodowska-Curie Actions Individual Fellowship (Widening) to advance research on tensor-based machine learning methods for affect modelling. Dr Makantasis has been recognized for his research excellence, including his inclusion in Stanford University’s World’s Top 2% Scientists List in 2023 and an extensive publication record, with 23 journal articles and 49 peer-reviewed conference papers in top-tier venues. His research focuses on the intersection of machine and statistical learning, image and signal processing, and computer vision, aiming to develop state-of-the-art methodologies for data analytics and decision-making technologies. Dr Makantasis values interdisciplinary collaboration and has worked with academic groups such as the KIOS Centre of Excellence at the University of Cyprus, the Institute of Digital Games at the University of Malta, and the Dynamical Systems and Simulation Laboratory at the Technical University of Crete, as well as industry partners including EXUS (UK), 7Reasons (Austria), and Massive Entertainment-Ubisoft (Sweden). His approach combines academic rigor with practical application, contributing to the advancement of artificial intelligence research and its real-world impact.
Senior Statistician, Central Bank of Malta, AI and Data Science expert. Focused on big data, machine learning and statistical processes.
Mr. Bilal Kurban is a seasoned data scientist and AI expert. He is currently a senior statistician in Central Bank of Malta. Before that he was leading the Artificial Intelligence and Data Analysis Unit at the Turkish Statistical Institute. He holds an M.Sc. in Data Science and a B.Sc. in Statistics. Throughout his career, Bilal has spearheaded numerous innovative projects including the implementation of big data analytics, machine learning algorithms and the development of AI-powered tools to enhance statistical processes. His expertise spans across data governance, business intelligence and the integration of administrative data into official statistics. An internationally recognized professional, Bilal has contributed to UNECE workshops and published extensively on topics such as data collection methodologies and the use of administrative data in official statistics. Bilal has a strong background in data acquisition, administrative registers and statistical methodologies. Bilal's multifaceted skill set, combining technical prowess with strategic thinking, positions him as a key figure in the intersection of artificial intelligence, data science, official statistics and data governance.
Statistician, Central Bank of Malta, specialising in European financial data. Expert in AI and machine learning models for financial data.
Ms Priyanka Bairapura is a Statistician at the Central Bank of Malta, specializing in European financial and banking data. She holds a master’s degree in data science from Politecnico di Milano and completed an Erasmus exchange program at EPFL in Switzerland, broadening her exposure to advanced statistical and computational techniques. She also contributed to insights and modelling projects at ASML in the Netherlands, gaining practical experience in applying data science to complex, real-world problems. Priyanka brings a strong technical foundation in Python, SQL, and advanced statistical modelling, with expertise in designing and implementing AI and machine learning models for financial data. She has hands-on experience in software development, coding robust data pipelines, and creating scalable solutions for analytics and decision-making. In her role, Priyanka focuses on product development by collaborating with cross-functional teams to design and implement data-driven solutions that align with organizational goals. Beyond her technical abilities, she is a proactive problem solver with a keen eye for detail, thriving in dynamic environments where she can combine statistical theory with modern computational methods to drive efficiency and innovation. Passionate about AI, machine learning, and automation, Priyanka continuously explores ways to enhance data workflows, develop software solutions, and build models that generate actionable insights. Her collaborative approach ensures that data strategies translate into meaningful outcomes, supporting informed decisions within the financial sector.
Statistician, Central Bank of Malta, specializing in data analysis and modeling for financial data.
Roxanne Spiteri is a Statistician within the Statistical Collection and Information Management Office in the Statistics Department at the Central Bank of Malta, a position she has held since July 2025. She brings to this role two years of prior experience as an intern in the same department, during which she built a strong technical foundation in data analysis, modelling and statistical operations that support informed decision-making within the financial sector. A dedicated machine learning enthusiast with a particular interest in the intersection of statistical theory and modern computational methods, Roxanne is a graduate of the University of Malta, where she earned a Bachelor of Science (Honours) in Mathematics, Statistics and Operations Research. Her undergraduate dissertation, “Identifying Cyberattacks using Machine Learning Techniques,” focused on applying Neural Networks and Variable Importance techniques to detect malicious network traffic, contributing to the broader field of anomaly and outlier detection.
For more details on registrations and submissions for the Neural networks and deep learning, please first login to your account. If you do not have an account then you can create one below: